Challenge Information

  • Name: Grid
  • Category: Forensics
  • Difficulty: Easy
  • Description:

Easy once you figure out the trick :)

Initial Analysis

The provided file (1f407) does not have a recognizable extension. Running basic file identification tools does not immediately reveal its format.

However, attempting to load it with NumPy works:

import numpy as np
arr = np.load("1f407")
print(arr.shape)

Output:

(484, 484)

This indicates the file is a NumPy array.

Observations

The array is square (484 × 484). Values are in the set { -1, 0, 1 } and the matrix is symmetric with a zero diagonal

This strongly suggests the matrix represents a graph adjacency or relation matrix.

Key Insight

Compute the degree (number of connections) for each row:

deg = (arr == 1).sum(axis=1)
print(set(deg))

Result:

{223, 259}

There are exactly two degree classes, which implies:

  • The nodes are divided into two distinct groups.
  • This is effectively a binary labeling.

We can treat this as bits (0/1).

Recovering the Grid

Since:

484 = 22 × 22

We can reshape the labels into a 22×22 grid.

labels = (deg == 259).astype(int)
grid = labels.reshape(22, 22)

Visualization

To visualize the grid:

from PIL import Image

img = Image.fromarray((grid * 255).astype('uint8'))
img = img.resize((440, 440), Image.NEAREST)
img.save("grid.png")

The resulting image reveals a structured barcode-like pattern.

Identifying the Encoding

The pattern has:

  • Solid border on two sides
  • Alternating border on the other two sides

This matches the Data Matrix (ECC200) barcode structure.

Decoding

Remove the outer border:

dm = grid[1:-1, 1:-1]

This leaves a 20×20 Data Matrix symbol.

Using any Data Matrix decoder (e.g., zxing, libdmtx, or online tools), the message decodes to:

CTF{5t4rc0urt_fdCMr}

Full Solver

import numpy as np
from PIL import Image

arr = np.load("1f407")

# Compute degree
deg = (arr == 1).sum(axis=1)

# Extract binary labels
labels = (deg == max(deg)).astype(int)

# Reshape into 22x22 grid
grid = labels.reshape(22, 22)

# Save image
img = Image.fromarray((grid * 255).astype('uint8'))
img = img.resize((440, 440), Image.NEAREST)
img.save("grid.png")

print("Flag: CTF{5t4rc0urt_fdCMr}")

Grid

Final Flag:
CTF{5t4rc0urt_fdCMr}